Compliance Persona: Model Owner or MLOps Lead

Model Monitoring & Drift Detection

Article 61 requires active performance monitoring throughout an AI system's lifetime. VDF AI Compliance compares live metrics to deployment baselines and triggers alerts, fallback routing, and incident drafts on breach.

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The Challenge

Why This Workflow Breaks Down

Models trained on 2023 data degrade on 2026 data as distributions shift. Only 11% of job postings mention post-market monitoring — yet Article 61 is mandatory for all high-risk systems. Compliance does not end at deployment.

How VDF AI Handles It

Governed Agents for Repeatable Execution

Baseline fairness and performance metrics from deployment are stored as the reference. After each production batch, current outputs are re-evaluated. If metrics breach configured thresholds, the system routes to a fallback model, drafts an Article 72 serious incident report, and notifies the compliance officer.

Agent Workflow

How the Agent Network Works

1

Baseline Capture

Records fairness and performance metrics at deployment as the reference point.

2

Continuous Evaluation

Re-runs the same criteria against live model outputs on a defined schedule.

3

Drift Detection

Compares current metrics to baseline and applies configurable thresholds.

4

Incident Response

Triggers fallback routing, incident report drafts, and officer notification.

Outcomes

Measurable Benefits

  • Continuous Monitoring Dashboard per AI system and metric
  • Drift alert configuration per regulatory threshold
  • Automated Article 72 Serious Incident Report draft on breach
  • Post-Market Monitoring Plan per high-risk system (Article 61 compliant)
Governance Fit

Security, Auditability, and Control

Covers EU AI Act Art. 61, Art. 72, ISO 42001 Clause 9, and NIST AI RMF MANAGE 4.1 with longitudinal metric storage.

Typical Integrations

Production model endpointsMonitoring dashboardsNotification systemsIncident management tools
Related Use Cases

Explore Adjacent Workflows

FAQ

Common Questions

What is Model Monitoring & Drift Detection?

Continuous post-deployment monitoring that tracks fairness and performance against baselines, alerts on degradation, and prepares serious incident documentation.

Is this required under the EU AI Act?

Yes — Article 61 requires providers of high-risk systems to establish post-market monitoring throughout the operational lifetime.

What happens when drift is detected?

Configurable responses include alerts, automatic fallback to an approved model, and draft Article 72 serious incident reports for compliance review.

How does this connect to fairness auditing?

Fairness audits establish the baseline metrics that drift monitoring tracks over time.

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